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Demand Response (DR) is an effective method for electricity coservation. Time-based demand response is basically based on general categorization of consumers including industrial, agricultural, commercial, and residential subscribers. Due to identicalness of  tariffs within each category,  time-based (PTB) demand response generally leads toexcessive load transfer. In this paper, with the subcategorization of each category and introduction of different tariffs for each subcategory, a new type of time-based demand response is introduced. It is expected that this proposal will lead to better consumption pattern within subcategories as well as its encompassing category.   To validate the proposed scheme we have used real data for the case of glass and cement industries. Genetic algorithms and particle swarm are used to optimize the objective function. Usind data garnered from energy audits in these industries and categorizing  load data in accordance to their time of use, it has been concluded that demand response tariffs can result into load shifts and reduced  electricity consumption.